Distributed Kalman-Consensus Filtering for Sparse Signal Estimation. (23rd March 2014)

• Record Type: Journal Article
• Authors: Liu, Yisha; Yu, Haiyang; Wang, Jian
• Other Names: Guo Ge Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2014(2014)
• Publication Date: 2014-03-23
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2014/138146
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : A Kalman filtering-based distributed algorithm is proposed to deal with the sparse signal estimation problem. The pseudomeasurement-embedded Kalman filter is rebuilt in the information form, and an improved parameter selection approach is discussed. By introducing the pseudomeasurement technology into Kalman-consensus filter, a distributed estimation algorithm is developed to fuse the measurements from different nodes in the network, such that all filters can reach a consensus on the estimate of sparse signals. Some numerical examples are provided to demonstrate the effectiveness of the proposed approach.